Automated selective caching for reference attribute grammars
Söderberg, Emma LU
and Hedin, Görel
LU
(2011)
SLE'10: 3rd International Conference on Software Language Engineering
6563.
p.2-21
- Abstract
- Reference attribute grammars (RAGs) can be used to express semantics as super-imposed graphs on top of abstract syntax trees (ASTs). A RAG-based AST can be used as the in-memory model providing semantic information for software language tools such as compilers, refactoring tools, and meta-
modeling tools. RAG performance is based on dynamic attribute evaluation with caching. Caching all attributes gives optimal performance in the sense that each attribute is evaluated at most once. However, performance can be further improved by a selective caching strategy, avoiding caching overhead where it does not pay off. In this paper we present a profiling-based technique for automatically finding a good caching configuration. The technique... (More) - Reference attribute grammars (RAGs) can be used to express semantics as super-imposed graphs on top of abstract syntax trees (ASTs). A RAG-based AST can be used as the in-memory model providing semantic information for software language tools such as compilers, refactoring tools, and meta-
modeling tools. RAG performance is based on dynamic attribute evaluation with caching. Caching all attributes gives optimal performance in the sense that each attribute is evaluated at most once. However, performance can be further improved by a selective caching strategy, avoiding caching overhead where it does not pay off. In this paper we present a profiling-based technique for automatically finding a good caching configuration. The technique has been evaluated on a generated Java compiler, compiling programs from the Jacks test suite and the DaCapo benchmark suite. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1671250
- author
- Söderberg, Emma
LU
and Hedin, Görel
LU
- organization
- publishing date
- 2011
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Lecture Notes in Computer Science
- editor
- Malloy, Brian ; Staab, Steffen and van den Brand, Mark
- volume
- 6563
- pages
- 2 - 21
- publisher
- Springer
- conference name
- SLE'10: 3rd International Conference on Software Language Engineering
- conference dates
- 2010-10-12
- external identifiers
-
- wos:000296827000002
- scopus:79952265753
- ISBN
- 978-3-642-19439-9
- DOI
- 10.1007/978-3-642-19440-5_2
- project
- Embedded Applications Software Engineering
- language
- English
- LU publication?
- yes
- id
- c5b1fa14-9667-4779-b1eb-6904c3967be2 (old id 1671250)
- date added to LUP
- 2016-04-04 11:00:10
- date last changed
- 2022-04-08 06:31:26
@inproceedings{c5b1fa14-9667-4779-b1eb-6904c3967be2,
abstract = {{Reference attribute grammars (RAGs) can be used to express semantics as super-imposed graphs on top of abstract syntax trees (ASTs). A RAG-based AST can be used as the in-memory model providing semantic information for software language tools such as compilers, refactoring tools, and meta-<br/><br>
modeling tools. RAG performance is based on dynamic attribute evaluation with caching. Caching all attributes gives optimal performance in the sense that each attribute is evaluated at most once. However, performance can be further improved by a selective caching strategy, avoiding caching overhead where it does not pay off. In this paper we present a profiling-based technique for automatically finding a good caching configuration. The technique has been evaluated on a generated Java compiler, compiling programs from the Jacks test suite and the DaCapo benchmark suite.}},
author = {{Söderberg, Emma and Hedin, Görel}},
booktitle = {{Lecture Notes in Computer Science}},
editor = {{Malloy, Brian and Staab, Steffen and van den Brand, Mark}},
isbn = {{978-3-642-19439-9}},
language = {{eng}},
pages = {{2--21}},
publisher = {{Springer}},
title = {{Automated selective caching for reference attribute grammars}},
url = {{http://dx.doi.org/10.1007/978-3-642-19440-5_2}},
doi = {{10.1007/978-3-642-19440-5_2}},
volume = {{6563}},
year = {{2011}},
}